A loss function measures how far apart the current model is from the provided data. We'll useastandard loss model forlinear regression,which sums the squares of the deltas between the current model andthe provided data.linear_model-ycreatesavector where eachelement isthe corresponding example's error delta. We call tf.square to square that error. Then, we sum all the squared errors to create a single scalar that abstracts the error of all examples using tf.reduce_sum